Workshop on Co-Development of Computer Science and Law

Virtual - Nov. 10-12, 2020

Register here.

Date: 12:00pm-5:00pm ET November 10, 11, and 12, 2020

Location: Online Event; Participants Must Register by November 6, 2020, to Attend

Workshop Description

Sophisticated computation, embedded in a variety of sociotechnical systems, has become an essential enabler of everyday life. As such systems have become more powerful and more present, the interdisciplinary research area of computer science and law has begun to take shape. This workshop will explore the establishment of rigorous foundations for this emerging interdisciplinary area. It will focus on the need for co-development of computational techniques and legal principles, using the strengths of each approach to compensate for known weaknesses in both and building shared understanding, methodology, and vocabulary to improve communication and catalyze research across the two disciplines.

The workshop will consider how to create technical definitions and solutions in concert with the creation of legal language so that the two fields can work together to solve or proactively prevent problems. Ideally, computer scientists and lawyers should collaborate to create legislative language and technical definitions that are consistent and that capture broadly agreed-upon principles. For example, technical considerations and definitions embedded in legislation should reflect what is technically feasible and not mandate impossible requirements, while implementations of such requirements should produce sufficient evidence that their behavior sits within stated requirements and thus complies with the law.

The workshop will be a next step in the development of a research community in computer science and law that brings together computer scientists, statisticians, law scholars, and social scientists studying sociotechnical assemblages and their governance.

Program Preview:
Ran Canetti (Boston University):
Automated Contact Tracing: Individualism, Society, Law and Technology in an Aerosol Droplet

Aloni Cohen (Boston University):
What a Hybrid Legal-Technical Analysis Teaches Us About Privacy Regulation: The Case of Singling Out

Hany Farid (University of California at Berkeley):
Assessing the Reliability of Clothing-Based Forensic Identification

Marilyn George (Brown University):
Surveillance, Privacy and Social Control

James Grimmelmann (Cornell University):
CPU, Esq: Should Law Be More Like Software?

Katrina Ligett (Hebrew University) & Kobbi Nissim (Georgetown University):
Data Co-Ops: Challenges, and How to Get There

Sarah Scheffler (Boston University):
Protecting Cryptography Against Compelled Self-Incrimination

Mayank Varia (Boston University):
Where can Law Help to Address Aspects of Privacy that Technology Cannot on its Own?

Daniel Weitzner (Massachusetts Institute of Technology):
What Cybersecurity Policy Would Look Like if We Could Actually Measure Cyber Risk

Jonathan Zittrain (Harvard University):
Intellectual Debt: What's Wrong When Machine Learning Gets It Right

The full program will be published on the workshop website:

This will be an online workshop.
Attendance is free and open to the public, but registration is required. In addition to invited talks, the event will include contributed lightning talks and a contributed poster session.

To attend, register by November 6, 2020:

To submit a poster or lightning talk, enter the required information by November 2, 2020:

Depending on the number of posters submitted, the organizers may not select all submissions for presentation. Notifications will be sent by November 5, 2020.

If you have questions about the workshop, email Nicole Clark-Johnson <>
 and David Pennock <>.

Fairness, Accountability, and Transparency in Machine Learning -

Tuesday, November 10, 2020 - 12:00pm to Thursday, November 12, 2020 - 5:00pm